Apache Spark & Scala Certification Training Program

Classroom Training and Live Online Courses

Wichita, KS

Stop bottlenecking your data processing. Get the mandatory credential that proves you can build lightning-fast, highly scalable analytics engines in Spark and command the top salary bracket for Big Data Engineers.

  • Master Spark Internals (DAG, Catalyst)
  • Achieve Functional Scala Fluency
  • Optimize DataFrames & Spark SQL
  • Implement Spark Streaming & MLlib
  • End-to-End Analytics Deployment
  • 2000+ Performance Debugging Scenarios
  • Native Scala for Native Spark Speed
  • 24x7 Expert Code Optimization Support
  • Apache Spark & Scala Certification Training Program Overview Wichita, KS

    Your current data infrastructure struggles with growing volumes. Batch processes take hours, and management demands real-time insights - a need your legacy ETL or Python setup cannot meet. Modern Apache Spark-driven big data roles in Wichita, KS and other competitive markets require engineers who can design high-performance, fault-tolerant pipelines using Scala. Without skills in Spark, Scala, and DataFrame Optimization, HR filters reject your resume from high-paying Senior Data Engineer and Machine Learning Engineer positions. This program equips you to solve billions of real-time events efficiently. This isn't a basic apache spark tutorial. Our Apache Spark course is designed by experienced Big Data Architects managing multi-terabyte Spark clusters in Wichita, KSFintech and Telecom sectors. You'll master core performance concepts like handling skew, optimizing joins, managing garbage collection, and understanding when to use RDDs versus DataFrames - insights drawn from apache spark documentation and apache spark architecture best practices. Through hands-on labs with Spark Shell and advanced IDEs, you'll tackle real-world apache spark big data projects such as collaborative filtering and large-scale SQL queries. This apache spark certification ensures you're ready for top apache spark interview questions and positions you for sub-second response systems critical in modern enterprises.

    Apache Spark & Scala Certification Course Highlights in Wichita, KS

    Deep-Dive into Spark Internals

    Mandatory modules on the Spark execution flow, DAGScheduler, TaskScheduler, and Memory Management to ensure you can optimize any job.

    Mastery of Advanced Spark Components

    Dedicated hands-on training in Spark Streaming, MLlib (Machine Learning), and GraphX for complete, full-spectrum application development.

    2000+ Performance-Focused Questions

    Our question bank is engineered to test your ability to debug performance issues, select optimal Spark/Scala syntax, and choose the best data structure for the task.

    Rigorous Scala Programming Fluency

    Achieve the required level of Scala competence to write concise, functional, and enterprise-grade code, maximizing Spark's native efficiency.

    End-to-End Optimization Techniques

    Learn the most critical optimization skills: caching strategies, serialization choices (Kryo), and data partitioning to cut down execution time by orders of magnitude.

    24x7 Expert Guidance & Support

    Get immediate, high-quality help from certified Senior Data Engineers on complex code debugging, performance tuning, and architectural design questions.

    Growth

    The growth of big data and analytics has led to a critical need for scalable, in-memory data processing frameworks. Apache Spark & Scala Certification Training Program equips professionals with the tools to tackle complex data sets, leveraging functional programming principles and the versatility of Scala. By mastering Spark's core components, including Resilient Distributed Datasets (RDDs) and DataFrames, professionals can unlock unprecedented performance and scalability. Spark's core architecture relies on a novel abstraction called resilient distributed datasets (RDDs), which provide fault-tolerant, in-memory data processing.

    Scala's type system and strong focus on immutability enable developers to write robust, modular code. By applying the principles of Apache Spark, professionals can create data pipelines that seamlessly integrate with various data sources and sinks. In the data-driven economy of Wichita, KS, organizations require professionals who can harness big data to drive business insights. The Apache Spark & Scala Certification Training Program empowers data scientists, engineers, and analysts to develop scalable data processing solutions, fostering innovation and competitiveness in the industry.

    Professionals who have mastered Spark's DataFrames API can create complex queries using higher-order functions and lambda expressions, reducing the overhead of manual data manipulation. Data engineers who specialize in Apache Spark can optimize data processing pipelines for diverse workloads and data sources, ensuring data-driven decision making. In Wichita, KS's thriving tech industry, professionals who possess Apache Spark & Scala Certification Training Program credentials can capitalize on the growing demand for data-driven technologies. With expertise in Apache Spark, data professionals can build scalable, high-performance data processing systems, transforming business operations and driving organizational success.

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    Industry Applicability

    Apache Spark & Scala Certification Training Program is tailored to the needs of organizations operating in various industries, including finance, healthcare, and e-commerce. Professionals who grasp the principles of Spark's in-memory data processing can optimize data-intensive applications, such as real-time analytics and machine learning. By mastering Scala's object-oriented and functional programming paradigms, developers can create maintainable, efficient code for mission-critical systems. Spark's unified data processing engine supports various data formats, including SequenceFiles, Parquet, and JSON, enabling seamless data integration across disparate sources.

    Scala's concise syntax and high-level abstractions facilitate the creation of efficient data processing workflows. In industries where data drives strategic decision making, professionals with Apache Spark & Scala Certification Training Program expertise can unlock the full potential of their organization's data assets. In the data-driven economy of Wichita, KS, companies across various industries rely on Spark-based data processing solutions to drive innovation and growth. The Apache Spark & Scala Certification Training Program equips professionals with the skills to design and implement scalable, high-performance data architectures, meeting the evolving needs of organizations.

    Professionals with expertise in Apache Spark can develop and deploy data-intensive machine learning models using Spark MLlib, accelerating insights and driving business outcomes. Data engineers who specialize in Spark-based data warehousing and ETL can create high-performance data pipelines, enabling data-driven decision making. By achieving Apache Spark & Scala Certification Training Program credentials, professionals can demonstrate their expertise in designing, building, and optimizing data processing systems, aligning their skills with industry demand and driving career advancement.

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    Skills You Will Gain In Our Apache Spark & Scala Training Program in Wichita, KS

    Spark Core Mastery & RDDs

    Learn the foundational Spark architecture, lazy evaluation, and immutability. You will master RDD transformations and actions, understanding when this lower-level API is mandatory for complex tasks.

    Functional Scala Programming

    Achieve proficiency in the Scala language - including case classes, pattern matching, and functional constructs - to write clean, concurrent, and bug-resistant Spark applications.

    Spark SQL & DataFrame Optimization

    Master the highly efficient DataFrame/DataSet APIs. You will use Spark SQL for structured data, learning to leverage the Catalyst Optimizer for mandatory, high-speed query execution.

    Real-Time Data Streaming

    Go live. Implement Spark Streaming and Structured Streaming for continuous data processing, learning techniques for state management and handling event-time windows for accurate, real-time analytics.

    Distributed Machine Learning (MLlib)

    Deploy scalable ML models. You will use MLlib to implement algorithms like collaborative filtering and classification across massive datasets, turning raw data into predictive assets.

    Graph Processing (GraphX)

    Tackle complex network analysis. You will utilize GraphX for use cases like social network analysis and supply chain optimization, extending your skills to complex relationship data structures.

    Who This Program Is For

    Java/Python Developers (3+ years experience)

    ETL/BI Developers

    Big Data Engineers (Hadoop)

    Data Scientists

    Software Architects

    Technical Leads

    If your current job requires processing large datasets (TBs or PBs) and your code is bottlenecking, this rigorous training in Spark & Scala is your only path to high-performance computing, the Senior Engineer title, and the associated high salary.

    Work Responsibilities

    Professionals with Apache Spark & Scala Certification Training Program expertise are responsible for designing, building, and maintaining large-scale data processing systems. They collaborate with cross-functional teams to develop and implement data-driven solutions, leveraging Spark's unified data processing engine and Scala's high-level programming abstractions. In these roles, professionals apply Apache Spark's fault-tolerant, in-memory data processing capabilities to create scalable data pipelines, integrating with various data sources and sinks.

    They also apply Scala's concise syntax and high-level abstractions to optimize data processing workflows, reducing the overhead of manual data manipulation. In Wichita, KS's thriving tech industry, professionals with Apache Spark & Scala Certification Training Program expertise are in high demand. They work on building data-intensive applications, performing data analytics, and guiding data-driven decision making in various industries.

    Professionals with expertise in Apache Spark can develop and deploy real-time data processing applications using Spark Streaming, enabling timely insights and driving business outcomes. Data engineers who specialize in Spark-based data warehousing can create high-performance data pipelines, accelerating business decision making. By applying Apache Spark & Scala Certification Training Program concepts, professionals can improve their coding skills, data analysis capabilities, and problem-solving abilities, leading to enhanced career prospects and professional growth.

    Apache Spark & Scala Certification Training Program Roadmap in Wichita, KS

    1/7

    Why get Apache Spark & Scala certified?

    Stop getting filtered out by HR bots

    Get the senior-level, high-performance Data Engineer interviews your experience already deserves.

    Unlock the higher salary bands and specialized bonuses

    Reserved for engineers who can guarantee sub-second latency on massive-scale data.

    Transition from maintenance programmer to a high-impact architect

    Owning the execution engine that powers all enterprise analytics.

    Eligibility and Pre-requisites

    While vendor-neutral certification is less common, the most respected proofs of competence come from organizations like Databricks or Confluent, or simply the demonstrable capability honed by this program.

    Eligibility Criteria:

    Success hinges on:

    Mandatory Scala Proficiency: Demonstrable ability to write efficient, clean, and functionally correct Scala code is non-negotiable for writing optimized Spark applications.

    Spark Architectural Mastery: Proven deep understanding of the Spark execution model (DAG, memory, partitioning) and the trade-offs between RDDs, DataFrames, and DataSets.

    Hands-on Component Deployment: Mandatory experience in using Spark SQL for complex queries, Spark Streaming for real-time applications, and MLlib for distributed machine learning.

    Professional Credibility

    Professionals who achieve Apache Spark & Scala Certification Training Program credentials demonstrate a high level of expertise in designing, building, and optimizing large-scale data processing systems. Certified professionals have the skills to apply Apache Spark's unified data processing engine and Scala's high-level programming abstractions to meet the evolving needs of organizations. In the competitive tech industry, professionals with Apache Spark & Scala Certification Training Program expertise can differentiate themselves from their peers and enhance their professional credibility.

    By showcasing their skills in data-intensive systems and applications, certified professionals can demonstrate their value to employers and clients. In Wichita, KS's data-driven economy, professionals with Apache Spark & Scala Certification Training Program credentials are in high demand. They work on building data-intensive applications, performing data analytics, and guiding data-driven decision making in various industries.

    Certified professionals with expertise in Apache Spark can optimize data processing workflows, reduce data latency, and improve overall system performance. Data engineers who specialize in Spark-based data warehousing can create high-performance data pipelines, accelerating business decision making. By achieving Apache Spark & Scala Certification Training Program credentials, professionals can demonstrate their technical expertise, industry knowledge, and problem-solving abilities, showcasing their commitment to delivering high-quality data-driven solutions.

    Course Modules & Curriculum

    Module 1 Project Foundation & People Leadership
    Lesson 1: Project Management Mastery Framework

    If you're preparing for the PMP Certification, this structured course helps you master every topic defined in the PMP Exam Content Outline while building real-world leadership and project delivery expertise. Our PMP Training is aligned with PMI's latest framework and supports professionals meeting Project Management Professional certification requirements for both eligibility and exam success.

    Lesson 2: Leading High-Performance Teams

    Transform dysfunctional teams into productive units through proven leadership techniques. Develop skills in conflict resolution, team motivation, and performance management. Learn when to coach, when to direct, and how to maintain team morale during high-pressure situations.

    Lesson 3: Stakeholder Management & Influence

    Navigate complex stakeholder relationships and competing priorities with confidence. Master stakeholder analysis techniques, influence strategies, and negotiation tactics. Learn to manage difficult personalities and secure buy-in from resistant stakeholders without formal authority.

    Module 2 Planning Excellence
    Lesson 1: Scope Management Systems

    Scope management is the backbone of successful project execution - and a key topic covered in every Project Management Professional course online and in the PMP exam questions. Learn to define project boundaries with precision and prevent costly scope creep.

    Lesson 2: Schedule Development & Control

    Time management is one of the most heavily weighted areas in the PMP exam content outline. This lesson trains you to build and control project schedules that meet deadlines without sacrificing quality.

    Lesson 3: Cost Management & Earned Value

    Develop accurate cost estimates using proven methodologies and track real project performance through Earned Value Management. Learn to create meaningful budgets, analyze variances, and communicate financial status to stakeholders in terms they understand and act upon.

    Module 3 Risk, Quality & Procurement
    Lesson 1: Risk Management Framework

    Identify what can derail your projects before it happens and build comprehensive response strategies. Master both qualitative and quantitative risk analysis techniques, including Monte Carlo simulations and decision trees that enable data-driven risk decisions.

    Lesson 2: Quality Management Systems

    Build quality into your processes rather than inspecting it later. Learn the difference between quality planning, assurance, and control. Master quality tools like control charts and Pareto analysis to drive continuous improvement and prevent costly rework.

    Lesson 3: Procurement & Contract Management

    Procurement is a key area of the Project Management Professional exam and essential to professional project delivery. Learn to manage vendor contracts, conduct negotiations, and select the right contract types. This PMP course online module teaches practical approaches to vendor evaluation, risk allocation, and performance monitoring, ensuring your projects stay on schedule and within budget.

    Module 4 Execution & Monitoring
    Lesson 1: Project Execution Leadership

    Lead project teams through successful delivery while managing resources, resolving issues, and maintaining momentum. Learn to direct project work effectively, acquire and develop team members, and create reporting systems that inform rather than overwhelm stakeholders.

    Lesson 2: Monitoring & Control Systems

    Implement control systems that catch problems early and enable corrective action. Master integrated change control procedures, performance measurement techniques, and variance analysis methods that keep projects on track and stakeholders informed.

    Lesson 3: Agile & Hybrid Approaches

    Modern project management requires agility. This PMP certification course explores agile, predictive, and hybrid delivery approaches - helping you understand when and how to apply each. Learn Scrum ceremonies, Kanban flow metrics, and hybrid governance techniques that integrate flexibility into traditional structures. These topics are a major part of the current Project Management Professional exam content outline, making this lesson essential for every PMP-certified professional.

    Module 5 Closing & Exam Preparation
    Lesson 1: Project Closing & Professional Responsibility

    Execute proper project closure procedures and understand your ethical obligations as a certified project management professional. Learn to capture lessons learned effectively, manage contract closure, and navigate ethical dilemmas using the PMI Code of Ethics.

    Lesson 2: Exam Strategy & Practice

    Develop test-taking strategies specifically designed for the PMP exam format. Learn question analysis techniques, time management strategies, and how to approach situational questions that test your judgment rather than just knowledge recall.

    Lesson 3: Final Review & Certification Readiness

    This capstone lesson brings everything together. You'll review every process group, knowledge area, and agile concept included in the PMP course online curriculum. Our instructors guide you through final assessments, identify weak areas, and ensure full exam readiness.

    Module 6 Spark Fundamentals
    Lesson 1: Introduction to Spark Architecture

    Understand the limitations of MapReduce and the rise of in-memory computing with Apache Spark. Master the Spark cluster components: Driver, Executor, Cluster Manager, and the critical DAGScheduler. This foundational lesson is essential for any apache spark course or apache spark certification candidate.

    Lesson 2: Introduction to Programming in Scala

    Master the functional programming fundamentals of Scala, including immutable variables, functions, closures, and the use of the Scala REPL/IDE for development.

    Lesson 3: Advanced Scala Functional Programming

    Dive deeper into Scala for Spark with case classes, pattern matching, collections, and higher-order functions. Mastering these concepts ensures you can write concise, high-performance distributed code, aligning with best practices from apache spark documentation and advanced apache spark tutorials.

    Module 7 Spark Core and RDD Mastery
    Lesson 1: Using RDD for Creating Applications in Spark

    Master the core Resilient Distributed Dataset (RDD) API. Understand fault tolerance, partitioning, and caching, the foundation for all Spark computations.

    Lesson 2: RDD Transformations and Actions

    Hands-on implementation of the core RDD operations: map, filter, reduceByKey, join, and their critical distinction between narrow and wide dependencies.

    Lesson 3: Spark Optimization and Performance Tuning (Core)

    Learn mandatory core optimization: choosing the correct Storage Level, using Kryo Serialization for speed, and managing the critical trade-offs between partitioning and memory.

    Module 8 Structured Data and Spark SQL
    Lesson 1: Running SQL Queries Using Spark SQL

    Master Apache Spark SQL by creating and using DataFrames and DataSets. Understand their memory-efficient, strongly-typed nature and how structured data improves performance in apache spark big data projects. This lesson is essential for apache spark course participants preparing for apache spark certification.

    Lesson 2: The Catalyst Optimizer and Query Tuning

    Deep dive into the Catalyst Optimizer and Tungsten execution engine. Learn how to interpret query plans, debug performance, and select the optimal join strategies.

    Lesson 3: Advanced DataFrame Operations and Window Functions

    Master complex DataFrame manipulations including UDFs (User-Defined Functions) and advanced windowing functions for rolling aggregations and ranking. This expertise is vital for enterprise reporting and real-world apache spark big data applications.

    Module 9 Streaming and Machine Learning
    Lesson 1: Spark Streaming and Structured Streaming

    Understand the difference between micro-batching and continuous processing. Implement Structured Streaming for fault-tolerant, end-to-end real-time pipelines.

    Lesson 2: Distributed Machine Learning with Spark MLlib

    Master the MLlib API. Implement and evaluate core algorithms like Linear Regression, Logistic Regression, and Collaborative Filtering across large-scale datasets.

    Lesson 3: Feature Engineering and ML Pipeline

    Learn the mandatory steps of building a robust ML pipeline: feature selection, scaling, model training, and persistent storage of models for deployment.

    Module 10 GraphX, Ecosystem, and Production Readiness
    Lesson 1: Spark GraphX Programming

    Master the GraphX API in Apache Spark for advanced graph analysis. Implement algorithms like PageRank and community detection for applications in social networks, telecom, and other apache spark big data projects. This is a key skill for apache spark certification and apache spark interview questions.

    Lesson 2: Ecosystem Integration and Deployment

    Connect Spark with external systems: Kafka for ingestion, HDFS/S3 for storage, and Hive/Impala for querying. Master deployment on YARN or Kubernetes.

    Lesson 3: Production Tuning and Debugging

    Master production-level skills including cluster sizing, monitoring with Prometheus, memory and garbage collection management, and interpreting Spark UI metrics. These advanced capabilities are essential for real-world apache spark course participants and high-value apache spark certification candidates.

    Apache Spark & Scala Certification & Exam FAQ

    Which specific Spark certification does this course prepare me for?
    This program provides the high-level, practical skills necessary to succeed in vendor-specific exams like the Databricks Certified Associate Developer (using Scala or Python) and similar professional-level certifications focused on performance.
    How much does the Databricks Certified Associate Developer exam cost?
    The exam fee for the Databricks certification is typically around $200 to $300. This external fee must be budgeted for in addition to your training cost.
    Is the Spark certification a theoretical or a performance-based exam?
    Most modern, high-value Spark certifications are performance-based. You are typically required to write, debug, and optimize code in a hosted environment under a strict time limit. Our labs mimic this reality.
    How many questions are on the Spark exam and how long do I have?
    For practical exams, you typically face 40-60 tasks/questions over a duration of 90 to 120 minutes. The pressure is high; accuracy and speed are non-negotiable.
    What is the passing score for the Spark certification?
    The required passing score is typically around 70% to 75%. Our program is structured to push you consistently past 85% in all mock performance assessments.
    Why is Scala mandatory, and can I use Python (PySpark) instead?
    Scala is mandatory because it is Spark's native language, offering superior performance and elegance for production code. While PySpark is supported, mastering Scala provides a deeper understanding and is often preferred for high-performance enterprise solutions.
    Do I need to memorize the entire Spark API syntax?
    No. You must internalize the logic and architectural differences (RDD vs. DataFrame) and the correct parameters for performance functions like cache() and repartition(). The logic matters more than the exact syntax.
    Can I take the Spark certification exam online from home?
    Yes. Most exams are offered via online proctoring. Be warned: the environment and internet stability requirements are extremely strict. We recommend using a stable testing center in major Wichita, KScities if possible.
    What is the role of the Catalyst Optimizer?
    The Catalyst Optimizer is Spark SQL's brain. It automatically performs query optimizations (like predicate pushdown) and execution plan creation, ensuring your DataFrame/SQL code runs as fast as possible. You must understand how to leverage it.
    How long is the Apache Spark certification valid?
    Most vendor-specific Spark certifications are valid for two years. You must recertify to prove your competence is current with the rapidly evolving features and performance updates.
    How does this course handle complex troubleshooting like data skew?
    We include dedicated lab scenarios where we introduce data skew (uneven data distribution) and teach you the mandatory techniques to fix it, such as strategic salting and broadcast joins.
    Is a full Hadoop cluster required to run Spark applications?
    No. Spark can run locally or on a standalone cluster. However, in production, it is typically deployed on a cluster manager like YARN (Hadoop) or Kubernetes to manage resources. We cover both deployment models.
    What are DataFrames, and why are they better than RDDs?
    DataFrames are an abstraction built on RDDs. They are faster because they allow Spark to optimize execution (via Catalyst) and they use memory-efficient storage, making them the standard for modern, high-performance data engineering.
    What is the critical difference between cache() and persist() in Spark?
    cache() stores data in memory only (default StorageLevel), while persist() allows you to choose a specific storage level (e.g., MEMORY_AND_DISK). Misusing these leads to massive performance penalties.
    Does the program cover Spark integration with Delta Lake or other storage layers?
    Yes. We cover the integration of Spark with modern data lake formats and cloud storage (e.g., S3/ADLS) as it's the non-negotiable production environment for today's data engineering roles.

    Skill Development

    Apache Spark & Scala Certification Training Program empowers professionals with the skills to design, build, and optimize large-scale data processing systems. The program covers topics such as Spark's unified data processing engine, Scala's high-level programming abstractions, and data-intensive applications development. In these roles, professionals develop skills in data processing, data analytics, and problem-solving, applying Apache Spark's fault-tolerant, in-memory data processing capabilities and Scala's concise syntax.

    They also learn to optimize data processing workflows, reduce data latency, and improve overall system performance. In Wichita, KS's thriving data-driven economy, professionals with Apache Spark & Scala Certification Training Program expertise can build a strong foundation in data-intensive systems and applications. By mastering Apache Spark and Scala, professionals can improve their coding skills, data analysis capabilities, and problem-solving abilities.

    Professionals with expertise in Apache Spark can develop and deploy real-time data processing applications using Spark Streaming, enabling timely insights and driving business outcomes. Data engineers who specialize in Spark-based data warehousing can create high-performance data pipelines, accelerating business decision making. By participating in the Apache Spark & Scala Certification Training Program, professionals can enhance their technical expertise, industry knowledge, and problem-solving abilities, leading to enhanced career prospects and professional growth.

    Customer Testimonials

    Course & Support

    How long does the training take to complete?
    The Apache Spark course follows an intensive 5-week schedule to build deep technical and architectural competence in apache spark architecture and apache spark big data processing.
    What are the prerequisite skills for enrolling in this training?
    You should have 3+ years of experience in core Java or Python, along with solid foundational knowledge of SQL and basic data structures, preparing you for real-world apache spark projects.
    Are the coding labs done on my local machine or a provided environment?
    Labs are conducted on a dedicated, cloud-based Spark cluster (Databricks-like environment) provided by us. This ensures a consistent, high-performance setup without complex local configuration issues.
    What if I miss a scheduled live class session?
    Every session is recorded in high-quality video and uploaded within 24 hours. You can also re-attend the same session in any future live batch at no extra cost.
    How flexible is the program if my professional schedule shifts mid-course?
    Highly flexible. You can pause your access for up to 6 months and rejoin any running batch, ensuring your investment is protected from unexpected project demands.
    Who are the instructors?
    Our instructors are Senior Data Architects and ML Engineers with 8+ years of experience, specializing in Scala/Spark optimization and deployment for massive-scale Wichita, KSenterprises.
    What is the maximum class size for the live sessions?
    Classes are capped at 25 participants to ensure personalized code reviews, performance profiling, and direct interaction with instructors?key for preparing for apache spark interview questions.
    Is there a difference in content between the weekday and weekend batches?
    No. The core content, hands-on labs, optimization modules, and instructor expertise are identical across all scheduling formats.
    Do I need any special software installed locally?
    Only an IDE (like IntelliJ IDEA or VS Code) for writing Scala/Spark code, and a standard web browser for the class and cloud environment access.
    Is this training valid for candidates outside Wichita, KS?
    Yes. Apache Spark and Scala are global standards for high-performance computing, making our apache spark course relevant and accessible worldwide.
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